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This paper proposes a formal cognitive agent model to address the critical gap in cross-agent coupling within human-AI teams, specifically targeting industrial environments where distributed cognition is essential. By defining eight core components including world models and memory, it establishes a theoretical foundation for designing cognitively interoperable systems that can co-regulate their decision-making cycles. This research advances the understanding of multi-agent coordination beyond simple task execution to include aligned perception and planning.
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An Agent Model Abstraction for Human-AI Teaming Cognitive Coupling

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arXiv:2609.05552v1 Announce Type: cross Abstract: Industrial environments increasingly rely on collaboration between humans and AI-enabled agents. Effective teamwork requires aligning how agents perceive situations, plan actions to pursue goals, and adapt to changing conditions, yet existing systems lack mechanisms for cross-agent cognitive processes coupling. This paper presents a conceptual cognitive agent model that formalises cognitive coupling through eight components: Input, Process, Output, State, Value, Memory, World Model, and Goal. The model abstracts how agents coordinate and co-regulate their cognitive cycles, providing a basis for analysing distributed cognition and designing cognitively interoperable human-AI systems.

Abstract:Industrial environments increasingly rely on collaboration between humans and AI-enabled agents. Effective teamwork requires aligning how agents perceive situations, plan actions to pursue goals, and adapt to changing conditions, yet existing systems lack mechanisms for cross-agent cognitive processes coupling. This paper presents a conceptual cognitive agent model that formalises cognitive coupling through eight components: Input, Process, Output, State, Value, Memory, World Model, and Goal. The model abstracts how agents coordinate and co-regulate their cognitive cycles, providing a basis for analysing distributed cognition and designing cognitively interoperable human-AI systems.

Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)

arXiv:2609.05552 [cs.HC]

(or arXiv:2609.05552v1 [cs.HC] for this version)

https://doi.org/10.48550/arXiv.2609.05552 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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